We are experiencing unprecedented growth in the numbers of individuals at risk for, or living with cancer due to population aging, greater use of early detection, advances in treatment, and increasing lifespan. By 2030, nearly 50% of the 45 million new cases and 75% of the 20 million cancer survivors will be aged 60 or older (older). Most of these older survivors are interested in and will benefit from systemic therapies. However, these treatments often have adverse effects on function, although data are largely from studies with younger survivors. Since only 4% of NCI-funded survivorship research specifically examines outcomes among older survivors, we know little about how the substantial heterogeneity in aging processes (biological age) affects risk for adverse functional outcomes among those of comparable chronological age. These data are important because they could affect treatment decisions, survivorship care planning, and ability to live independently. This Outstanding Investigator Award will use a bio-behavioral framework to conduct population sciences research at the intersection of cancer and aging to fill these gaps. Data, infrastructure, and established collaborations from an extant NCI-funded older cohort will be leveraged to iteratively build new studies to test novel hypotheses. Such cohorts are the population science equivalent of a basic science laboratory used for a series of experiments. The goals of the high-risk/high-reward studies are to: physical, emotional, social and role function; 1) define long-term trajectories of decline in cognitive, determine bio-behavioral risks for decline; and examine how systemic therapy and lifestyle factors moderate these relationships; 2) conduct exploratory research on biological age markers to determine feasibility and clinical utility for predicting ris and trajectory of functional decline; 3) conduct pilot randomized trials of the impact of lifestyle interventions on biological age markers and functional outcomes; and 4) enhance long-term clinical and policy impact by incorporating data into policy modeling, engaging survivors in design and communication of results, and supporting training. This research is innovative in use of a bio-behavioral framework and inclusion of policy modeling. The findings will move the field forward by shifting the paradigms of research and care for the growing older population; determining whether biological age markers can identify survivors at greatest risk for functional declines; informing future intervention trials; and expanding the limited number of cancer and aging researchers. The PIs history of productivity and strong institutional and collaborative support will ensure that the research will have the intended impact. Overall, the unique population science perspectives of these studies will add important diversity to the multi-disciplinary approaches needed for reducing the burden of cancer in older survivors.